Polish C++ operators documentation

[wangkuiyi]

We need to polish documentations of our operators. An example is

Paddle/paddle/operators/auc_op.cc

Lines 77 to 91 in 1363ddb

	AddComment(
	R"DOC(Computes the AUC according forward output and label.
	Best to use for binary classification evaluations.
	If input label contains values other than 0 and 1, it will be cast
	to bool.
	You can find the definations here:
	https://en.wikipedia.org/wiki/Receiver_operating_characteristic#Area_under_the_curve
	Possible curves are:
	- ROC: Receiver operating characteristic
	- PR: Precision Recall
	)DOC");
	}

We can take ONNX's documentation as a reference. This also helps us preparing joining ONNX.

The following operators' documentation needs polishment.

If you are going to file a PR to polish one or more of them, please check them so to avoid conflict of interests with others.

• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• accuracy_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• activation_op.cc
• adadelta_op.cc
• adagrad_op.cc
• adam_op.cc
• adamax_op.cc
• auc_op.cc
• batch_norm_op.cc
• cast_op.cc
• clip_op.cc
• concat_op.cc
• cond_op.cc
• conv2d_op.cc
• conv2dtranspose_op.cc
• conv_shift_op.cc
• cos_sim_op.cc
• crop_op.cc
• cross_entropy_op.cc
• decayed_adagrad_op.cc
• dropout_op.cc
• dynamic_recurrent_op.cc
• elementwise_add_op.cc
• elementwise_div_op.cc
• elementwise_mul_op.cc
• elementwise_op.h
• elementwise_sub_op.cc
• feed_op.cc
• fetch_op.cc
• fill_constant_batch_size_like_op.cc
• fill_constant_op.cc
• fill_zeros_like_op.cc
• gather_op.cc
• gaussian_random_op.cc
• gru_unit_op.cc
• huber_loss_op.cc
• increment_op.cc
• l1_norm_op.cc
• load_op.cc
• lookup_table_op.cc
• lrn_op.cc
• lstm_op.cc
• lstm_unit_op.cc
• margin_rank_loss_op.cc
• matmul_op.cc
• mean_op.cc
• minus_op.cc
• modified_huber_loss_op.cc
• momentum_op.cc
• mul_op.cc
• multiplex_op.cc
• nccl_op.cc
• nccl_op.cc
• nccl_op.cc
• nccl_op.cc
• pad_op.cc
• pool_op.cc
• pool_op.cc
• pool_with_index_op.cc
• pool_with_index_op.cc
• prelu_op.cc
• proximal_adagrad_op.cc
• proximal_gd_op.cc
• rank_loss_op.cc
• recurrent_op.cc
• reduce_op.cc
• reduce_op.cc
• reduce_op.cc
• reduce_op.cc
• reduce_op.cc
• reshape_op.cc
• rmsprop_op.cc
• save_op.cc
• scale_op.cc
• scatter_op.cc
• seq_expand_op.cc
• sequence_concat_op.cc
• sequence_conv_op.cc
• sequence_pool_op.cc
• sequence_softmax_op.cc
• sgd_op.cc
• sigmoid_cross_entropy_with_logits_op.cc
• sign_op.cc
• smooth_l1_loss_op.cc
• softmax_op.cc
• softmax_with_cross_entropy_op.cc
• split_op.cc
• squared_l2_distance_op.cc
• squared_l2_norm_op.cc
• sum_op.cc
• top_k_op.cc
• transpose_op.cc
• uniform_random_op.cc

[kavyasrinet]

Is anyone working on activation_op already ? If not I can start from there.

[kexinzhao]

Yes, I am working on them.

[kavyasrinet]

Alright! Thanks for the update. I will start from the other ones.

[kavyasrinet]

This has been successfully accomplished. Closing the issue.